[MUSIC] The previous module gave an introduction to cyber security in manufacturing in terms of, an information security framework, operational technology, and enterprise risk management. As it applies to creating a strong and secure DMD infrastructure. In this module, you will be introduced to the various components of the Digital Manufacturing Operation and we will discuss the basic security concepts that can be used to protect these components. Upon completion of this module you will be able to explain the digital manufacturing and design security concepts. Objectify the need of the security development life cycle model. State at least one secure programming practice. Discuss methods for protecting computer network and implementing appropriate authentication mechanisms. [MUSIC] Virtualization, artificial intelligence also called AI, and robotics are essential components of any modern digital process. The concept of virtualization, virtual computing, the generation of big data and the employment of AI, and robotics algorithms in DMD, will be described. Along with an illustration of how the entire digital manufacturing ecosystem works. Let us start with virtualization and virtual computing. The term virtualization refers to an asset which exists virtually and not physically. In terms of technology, virtualization refers to the creation of virtual computing resources with the help of software such as desktop, memory or operating system. The most common example of virtualization is operating system virtualization, which includes running multiple operating systems on a single host computer. An example would be running Linux operating system on a Windows laptop. The various types of virtualization are storage virtualization, network virtualization, desktop virtualization and application virtualization. Next is artificial intelligence, which is commonly referred to as AI. AI refers to machines which can mimic human cognitive skills such as learning and problem solving. Machines which can respond to a problem dynamically, without any manual feedback from a human, and can take actions on the basis of learned scenarios is an example of AI. Some of the recent examples of the exemplary use of AI are self driving cars, human face and voice recognition and Google's search engine. In digital manufacturing, AI has enormous applications. One scenario may be where machines are controlled remotely with the help of a simple mobile app. Another scenario may be where you have an alert system which can notify the user and can take necessary actions in case of emergency. Let us now talk about robotics. Robotics is a branch of engineering which involves conceptualizing, designing, manufacturing, and training robots. Robotics involves the continuation from many engineering fields, including computer science, electrical engineering, artificial intelligence, mechatronics and bio engineering. Robotics is a crucial part of digital manufacturing design since the Industry 4.0 revolution is based on the development of robotics and automation. Digital manufacturing is the current trend in manufacturing industry where the concept of cyber physical systems, Cloud computing and internet of things is introduced. It is also called the fourth industrial revolution and thus termed as industry 4.0. Industry 4.0 aims to forge information technology and operations technology together for developing a stronger manufacturing organization. The basic principles of Industry 4.0 is bringing all the machines, businesses, and other work pieces together in a single intelligent network, such that each asset can control or communicate with others in an autonomous manner. There are basically four digital manufacturing ecosystem design principles that define Industry 4.0. These are, one, interoperability. It is the ability of people, machines, and devices to communicate via a single platform or a network. Two, information transparency. It is the process of collecting physical world information using sensor devices. The data collected by sensors is raw data which is then processed to retrieve useful information to analyze the digital manufacturing system. Three, technical assistance. An efficient digital manufacturing system should be able to perform certain necessary operations including A, efficient automated trouble shooting that is quick response to problems by gathering and assessing sensor data. B, the ability to perform tedious computations or operations which may be infeasible to be performed by a human. Four, decentralized decisions. This is the ability of a cyber physical system to make decisions on its own to perform a competition. Only in the case of conflict or exception, control is given to higher levels, such system can be implemented using AI.
